Apparatus and method of performing user authentication

ABSTRACT

A user authentication apparatus trains a user authentication model by using biometric data of a user which was used in previous user authentication as training data, and performs user authentication by using the trained user authentication model.

TECHNICAL FIELD

The present disclosure relates to an apparatus and a method ofperforming user authentication.

BACKGROUND ART

For security, safety, privacy, and the like, electric devices mayinclude a user authentication function. User-created information such asa password or a pattern-type cryptography or intrinsic biometric data ofthe user such as an iris, fingerprint, and a blood vessel may be usedfor user authentication.

A user authentication apparatus, which performs user authentication byusing biometric data, may fail to correctly recognize a user due tocontamination of a sensor, changes in fingerprints, and the like.

DISCLOSURE Technical Solution

Provided are an apparatus and a method of performing user authenticationcapable of preventing a decrease in user recognition rates.

Provided is a method of performing user authentication, the methodincluding obtaining biometric data, performing user authentication basedon the obtained biometric data, adding the biometric data after userauthentication to training data, training a user authentication model byusing the training data, wherein the user authentication model is alearning model performing user authentication, obtaining new biometricdata, and performing user authentication based on the new biometric databy using the user authentication model.

The technical goals are not limited to the above, and other technicalgoals may be inferred from the following examples.

Advantageous Effects

A user authentication model is trained with respect to biometric databeing input in a process of using a user authentication apparatus, andthus, obstacles such as contamination of a sensor, change infingerprints, and the like may be reflected to training. Therefore, theuser authentication apparatus may perform user authentication to berobust to the obstacles by using the user authentication model.Accordingly, the user authentication apparatus may prevent decrease inuser recognition rates.

*8Effects of the present disclosure are not limited to the abovedescriptions, and more various effects are included in the presentspecification.

DESCRIPTION OF DRAWINGS

FIG. 1 shows an example of a user authentication apparatus;

FIGS. 2 through 4 show examples of user authentication methods;

FIGS. 5 through 10 show examples of methods of obtaining training data;

FIG. 11 shows a user authentication method according to an embodiment;

FIG. 12 is a block diagram showing a hardware configuration of anaerosol generating device;

FIG. 13 shows an example in which a user uses an aerosol generatingdevice; and

FIG. 14 shows an example of a method, performed by an aerosol generatingdevice, of authenticating a user.

BEST MODE

According to an embodiment, a method of performing user authenticationincludes: obtaining biometric data; performing user authentication basedon the obtained biometric data; adding the biometric data to trainingdata after the user authentication is performed; training, by using thetraining data, a user authentication model that is a learning modelconfigured to perform the user authentication; and obtaining newbiometric data and performing user authentication based on the newbiometric data by using the user authentication model.

The adding includes adding success biometric data to the training data,the success biometric data being the biometric data that succeeded inthe user authentication.

The adding includes adding previous biometric data to the training data,the previous biometric data being biometric data obtained before thesuccess biometric data is obtained.

The adding of the previous biometric data to the training data includesadding a predetermined number of the biometric data obtained immediatelybefore the success biometric data is obtained to the training data.

The previous biometric data may be biometric data obtained within apredetermined period before the success biometric data is obtained.

The adding of the previous biometric data to the training data includesadding a predetermined number of the previous biometric data obtainedwithin a predetermined period before the success biometric data isobtained.

The adding of the previous biometric data to the training data includesadding a plurality of pieces of the previous biometric data which aresequentially obtained to the training data, wherein each of a timeinterval between adding a piece of the previous biometric data to thetraining data and adding another piece of the previous biometric data tothe training data and a time interval between adding the successbiometric data to the training data and adding a piece of the previousbiometric data, obtained immediately before the success biometric data,to the training data is less than or equal to a predetermined timeinterval.

The adding includes adding similar biometric data to the training data,the similar biometric data being the biometric data and having asimilarity equal to or greater than a first reference value withreference data.

The performing of the user authentication includes determining that theuser authentication succeeded when similarity between the reference dataand the obtained biometric data is equal to or greater than a secondreference value, wherein the second reference value is a value greaterthan the first reference value.

The reference data is biometric data of the user obtained in advance foruser authentication, and the adding further includes adding thereference data to the training data.

The method may further include determining whether the userauthentication model needs to be trained based on a user recognitionrate of the user authentication model.

According to another embodiment, an apparatus for performing userauthentication includes: a sensor configured to obtain biometric data; amemory configured to store at least one program; and a controllerconfigured to perform user authentication by executing the at least oneprogram, the program includes instructions to implement operations of:performing user authentication on the obtained biometric data, addingthe biometric data to the training data after the user authentication,training, by using the training data, a user authentication model thatis a learning model configured to perform the user authentication,obtaining new biometric data, and performing user authentication basedon the new biometric data by using the user authentication model.

The apparatus further includes a battery; and a heater configured toreceive power from the battery and heat an aerosol generating material,and the controller controls power delivered from the battery to theheater.

The controller controls the power delivered to the heater, based on aresult of the user authentication.

The apparatus further includes an input interfacing element configuredto obtain a user input for controlling the device, and the controlleradds biometric data to the training data, the biometric data beingobtained from the input interfacing element after succeeding in userauthentication.

MODE FOR INVENTION

With respect to the terms used to describe the various embodiments,general terms which are currently and widely used are selected inconsideration of functions of structural elements in the variousembodiments of the present disclosure. However, meanings of the termscan be changed according to intention, a judicial precedence, theappearance of new technology, and the like. In addition, in certaincases, a term which is not commonly used can be selected. In such acase, the meaning of the term will be described in detail at thecorresponding portion in the description of the present disclosure.Therefore, the terms used in the various embodiments of the presentdisclosure should be defined based on the meanings of the terms and thedescriptions provided herein.

In addition, unless explicitly described to the contrary, the word“comprise” and variations such as “comprises” or “comprising” will beunderstood to imply the inclusion of stated elements but not theexclusion of any other elements. In addition, the terms “-er”, “-or”,and “module” described in the specification mean units for processing atleast one function and/or operation and can be implemented by hardwarecomponents or software components and combinations thereof.

As used herein, expressions such as “at least one of,” when preceding alist of elements, modify the entire list of elements and do not modifythe individual elements of the list. For example, the expression, “atleast one of a, b, and c,” should be understood as including only a,only b, only c, both a and b, both a and c, both b and c, or all of a,b, and c.

It will be understood that when an element or layer is referred to asbeing “over,” “above,” “on,” “connected to” or “coupled to” anotherelement or layer, it can be directly over, above, on, connected orcoupled to the other element or layer or intervening elements or layersmay be present. In contrast, when an element is referred to as being“directly over,” “directly above,” “directly on,” “directly connectedto” or “directly coupled to” another element or layer, there are nointervening elements or layers present. Like numerals refer to likeelements throughout.

Hereinafter, the present disclosure will now be described more fullywith reference to the accompanying drawings, in which exemplaryembodiments of the present disclosure are shown such that one ofordinary skill in the art may easily work the present disclosure. Thedisclosure can, however, be embodied in many different forms and shouldnot be construed as being limited to the embodiments set forth herein.

Hereinafter, embodiments of the present disclosure will be described indetail with reference to the drawings.

FIG. 1 shows an example of a user authentication apparatus.

A user authentication apparatus 1 may perform user authentication byusing biometric data. The user authentication apparatus 1 may be aseparate apparatus or an apparatus included in another device requiringa user authentication function. The user authentication apparatus 1 maybe used for opening and closing of entrances. Also, the userauthentication apparatus 1 may be used for user authentication foroperating devices such as a smart phone, a tablet device, a wearabledevice, a computer, and an electric cigarette. Also, the userauthentication apparatus 1 may be used for authority certification infields such as finance or national defense that require security.

The user authentication apparatus 1 may use various biometric data suchas fingerprint data, iris data, vein data, face shape data, palm printdata, voice data, and the like. Biometric data used by the userauthentication apparatus 1 is not limited to the data listed above. In auser authentication process, the user authentication apparatus 1 may useone type of biometric data or a plurality of types of biometric data.

The user authentication apparatus 1 may include a sensor 11, a memory12, and a controller 13.

The sensor 11 may be used for obtaining biometric data. The sensor 11may be an image sensor, a fingerprint sensor, an acoustic sensor, atemperature sensor, an electro-optical sensor, a bio sensor, anultrasonic sensor, but is not limited thereto.

The memory 12 may store the biometric data and at least one programexecuted by the controller 13. The program may include instructions thatimplement operations of the controller 13, which will be described indetail below. The memory 12 may be implemented as various types such asrandom access memory (RAM), for example, dynamic random access memory(DRAM), static random access memory (SRAM), and the like, read-onlymemory (ROM), or electrically erasable programmable read-only memory(EEPROM).

The controller 13 may comprise at least one processor. A processor canbe implemented as an array of a plurality of logic gates or can beimplemented as a combination of a general purpose microprocessor and amemory in which a program executable in the microprocessor is stored. Itwill be understood by one of ordinary skill in the art that theprocessor can be implemented in other forms of hardware.

The controller 13 may perform user authentication by using the biometricdata. The controller 13 may perform user authentication based on variousalgorithms.

For example, the controller 13 may compare similarity between thebiometric data and reference data, and may authenticate the user whenthe similarity is equal to or greater than a predetermined referencevalue. In this case, the reference data is data used to determinewhether the biometric data obtained in the process of using the userauthentication apparatus 1 is biometric data of the user.

For example, the controller 13 may compare the biometric data with thereference data based on a pattern recognition algorithm, a machinelearning algorithm, an image processing algorithm, a signal processingalgorithm, and the like.

For example, the controller 13 may perform user authentication by usinga learning model for machine learning. The user authentication apparatus1 may use a user authentication model that is a learning model forperforming user authentication. The user authentication model may bebased on a neural network such as a deep belief network and aconvolutional neural network, reinforcement learning, and the like, butis not limited to the above-listed types. The controller 13 may executeuser authentication by generating a user authentication model or loadinga user authentication model that is stored in advance in the memory 12.

Training data for the controller 13 to train or re-train the userauthentication model may include the reference data and the biometricdata obtained by the user authentication apparatus 1. The controller 13may train the user authentication model by using the training data andexecute user authentication by using the trained user authenticationmodel. The controller 13 may re-train the user authentication model byusing the training data and execute user authentication by using there-trained user authentication model.

The following user authentication methods may be performed by the userauthentication apparatus 1 of FIG. 1. Alternatively, the following userauthentication methods may be performed by the user authenticationapparatus 1 of FIG. 1 or other apparatuses.

FIG. 2 shows an example of a user authentication method.

In operation 201, the controller 13 obtains reference data. Thereference data may be the biometric data identified as biometric data ofthe user. The controller 13 may obtain the reference data through thesensor 11, load the reference data that is stored in advance in thememory 12, or obtain the reference data from other devices. Thereference data may be used later as a reference for determining whetherthe biometric data obtained by the user authentication apparatus 1 isthe biometric data of the user.

In operation 202, the controller 13 obtains biometric data via thesensor 11. For example, the reference data may correspond to a passwordset by the user, and the biometric data obtained by the controller 13 inoperation 202 may correspond to the password input by the user forauthentication in the process of using the user authentication apparatus1.

In operation 203, the controller 13 performs user authentication basedon the biometric data obtained in operation 202.

The controller 13 may perform user authentication by comparingsimilarity between the obtained biometric data and the reference data.For example, the controller 13 may compare similarity between thebiometric data and the reference data based on the pattern recognitionand then execute user authentication based on the comparison results.For example, the controller 13 may compare similarity between thebiometric data and the reference data based on the user authenticationmodel and then execute user authentication based on the comparisonresults.

The controller 13 may determine that the user authentication succeededwhen the similarity between the biometric data and the reference data isequal to or greater than a predetermined second reference value, and maydetermine that the user authentication failed when the similaritybetween the biometric data and the reference data is less than thesecond reference value.

FIG. 3 shows an example of a user authentication method.

In operation 301, the controller 13 obtains biometric data. Thecontroller 13 may obtain user's biometric data via the sensor 11.

In operation 302, the controller 13 performs user authentication basedon the obtained biometric data. The controller 13 may perform userauthentication by comparing similarity between the obtained biometricdata and the reference data. Various algorithms such as patternrecognition may be used for user authentication.

The controller 13 may perform user authentication based on the obtainedbiometric data, without using a user authentication model.Alternatively, the controller 13 may perform user authentication basedon the obtained biometric data by using the user authentication model.The user authentication model may be stored in advance in the memory 12.The user authentication model may be a learning model for machinelearning. For example, the user authentication model may be a neuralnetwork model or a reinforcement learning model, but it is not limitedthereto.

In operation 303, the controller 13 may add the biometric data which hasbeen used for the user authentication to the learning data. Thecontroller 13 may add success biometric data to the training data, thesuccess biometric data being biometric data that succeeded in userauthentication. The controller 13 may also add failure biometric data tothe training data, the failure biometric data being biometric data thatfailed in user authentication. In addition, the controller 13 may addthe reference data to the training data. Furthermore, the controller 13may add similar biometric data to the training data, the similarbiometric data having similarity equal to or greater than a firstreference value with the reference data. The first reference value maybe a predetermined value. The first reference value may be a valuesmaller than a second reference value that is a reference fordetermining the success biometric data.

The controller 13 may update training data with newly obtained biometricdata. For example, the controller 13 may replace the failure biometricdata, which is previously obtained, with the success biometric data thatis newly obtained.

The training data may be stored in the memory 12. Alternatively, thelearning data may be stored in a memory of another apparatus connectedto the user authentication apparatus 1. The other apparatus may be anapparatus communicating with the user authentication apparatus 1 in awireless or wired manner. For example, the user authentication apparatus1 may be an apparatus included in the aerosol generating device, and theother apparatus may be an external apparatus such as a smart phone orcomputer that may communicate with the aerosol generating device.

In operation 304, the controller 13 may train the user authenticationmodel by using the training data. Alternatively, the controller 13 mayre-train the user authentication model by using the training data.

For example, the user authentication model may be a deep neural network(DNN), and the controller 13 may train training parameters of the userauthentication model, such as a weight and a bias, by using the trainingdata. For example, the user authentication model may be a convolutionneural network (CNN), and the controller 13 may train the trainingparameters of the user authentication model such as weights of filters(or kernels) by using the training data. For example, the userauthentication may be a reinforcement learning model, and the controller13 may train the user authentication by using the training data tomaximize a reward or minimize a penalty.

Alternatively, other apparatus may train or re-train the userauthentication model by using the training data, and deliver the userauthentication model, after training or re-training, to the userauthentication apparatus 1.

In operation 305, the controller 13 may obtain new biometric data andperform user authentication based on the new biometric data by using theuser authentication model. In operation 305, the controller 13 mayperform user authentication by using the user authentication model thatis trained or re-trained in operation 304.

The user authentication model is trained not only with the referencedata but also with biometric data obtained in a user authenticationprocess, so it reflects changes occurring in a process of using the userauthentication device. Therefore, by performing user authenticationbased on new biometric data by using the user authentication model, theuser recognition failure of the user authentication device 1 may beprevented.

FIG. 4 shows an example of a user authentication method.

Operation 401 and operation 402 may respectively include characteristicsof operation 301 and operation 302 shown in FIG. 3.

In operation 403, the controller 13 determines whether the userauthentication succeeded. The controller 13 repeats operation 401 whenthe user authentication failed, and executes operation 404 when the userauthentication succeeded.

For example, the controller 13 may determine that the userauthentication succeeded when the similarity between the obtainedbiometric data and the reference data is equal to or greater than apredetermined second reference value, and may determine that the userauthentication failed when the similarity between the biometric data andthe reference data is less than the second reference value.

In operation 404, the controller 13 may add success biometric data tothe training data, the success biometric data being biometric data thatsucceeded in the user authentication. Various embodiments regardingoperation 404 will be described with reference to FIGS. 5 through 10.

FIG. 5 shows an example of obtaining training data.

The controller 13 may add the success biometric data to the trainingdata. For example, when fingerprint data is obtained five times for theuser authentication and fingerprint data obtained in a fifth order isthe success biometric data, the controller 13 may not add fingerprintdata obtained in first through fourth orders to the training data, asthe data is failure biometric data, and add the fingerprint data that isobtained in the fifth order to the training data.

The controller 13 may have the biometric data of the user included inthe training data by adding the success biometric data to the trainingdata.

FIG. 6 shows an example of a method of obtaining training data.

The controller 13 may add the success biometric data and previousbiometric data to the training data, the previous biometric data beingbiometric data obtained earlier than the success biometric data. Thecontroller 13 may add a predetermined number of pieces of previousbiometric data obtained immediately before the success biometric data tothe training data. For example, when the fingerprint data is obtainedfive times for user authentication, fingerprint data obtained in a fifthorder is success biometric data, and the predetermined number is three,the controller 13 may add second through fourth fingerprint data to thetraining data together with the success biometric data, the secondthrough fourth fingerprint data being three pieces of previous biometricdata.

FIG. 7 shows an example of a method of obtaining training data.

The controller 13 may add the success biometric data and the previousbiometric data to the training data. The controller 13 may add theprevious biometric data obtained in a predetermined period to thetraining data. The controller 13 may add the previous biometric data tothe training data, the previous biometric data obtained in apredetermined period before the success biometric data is obtained. Forexample, when fingerprint data obtained in a fifth order is successbiometric data, first through fourth fingerprint data is obtained twentyfive seconds, eighteen seconds, eight seconds, and three seconds beforeobtaining the fifth fingerprint data, respectively, and assuming thatthe predetermined period is twenty seconds, the controller 13 may addsecond through fourth fingerprint data to the training data, the secondthrough fourth fingerprint data being previous biometric data obtainedwithin twenty seconds before obtaining the success biometric data.

FIG. 8 shows an example of a method of obtaining training data.

The controller 13 may add the success biometric data and the previousbiometric data to the training data. The controller 13 may add thepredetermined number of pieces of previous biometric data obtained inthe predetermined period to the training data. For example, when thefingerprint data obtained in a fifth order is success biometric data,first through fourth data is obtained at twenty five seconds, eighteenseconds, eight seconds, and three seconds before obtaining the fifthfingerprint, respectively. Assuming that the predetermined number is twoand the predetermined period is twenty seconds, the controller 13 mayadd third through fourth previous biometric data to the training data,the third through fourth previous biometric data being previousbiometric data satisfying conditions, i.e., the predetermined number oftwo and the predetermined period of twenty seconds.

FIG. 9 shows an example of a method of obtaining training data.

The controller 13 may add the success biometric data and the previousbiometric data to the training data. The controller 13 may add theprevious biometric data obtained sequentially with a predetermined timeinterval to the training data. In this case, time intervals betweenpieces of the previous biometric data and between the success biometricdata and a piece of the previous biometric data obtained immediatelybefore the success biometric data among the plurality of pieces of theprevious biometric data may be less than or equal to a predeterminedtime interval.

For example, when fingerprint data obtained in a fifth order is successbiometric data, fourth fingerprint data is obtained one second beforeobtaining the fifth fingerprint data, third fingerprint data is obtained1.5 seconds before obtaining the fourth fingerprint data, secondfingerprint data is obtained 1.3 seconds before obtaining the thirdfingerprint data, first fingerprint data is obtained six seconds beforeobtaining the second fingerprint data, and the predetermined timeinterval is two seconds, the controller 13 may add the second throughfourth fingerprint data to the training data, as a time interval betweenobtaining the second through fourth fingerprint and next fingerprintdata is within two seconds, and may not add the first fingerprint datato the training data, as a time interval between obtaining the firstfingerprint data and the second fingerprint data exceeds two seconds.

FIG. 10 shows an example of a method of obtaining training data.

The controller 13 may add success biometric data and similar biometricdata to the training data, the similar biometric data being biometricdata having similarity equal to or greater than a first reference valuewith the reference data. The similar biometric data may be previousbiometric data or post biometric data that is biometric data obtainedafter the success biometric data. In this case, the first referencevalue may be a value smaller than a second reference value that is areference for determining the success biometric data. For example, whenfirst through fifth pieces of fingerprint data respectively havingsimilarities of 97%, 89%, 85%, 96%, and 99% to the reference data areobtained, and when the first reference value is 95% and the secondreference value is 99%, the controller 13 may add, to the training data,the fifth fingerprint that is success biometric data satisfying thesecond reference value and first and fourth pieces of fingerprint datathat are similar biometric data satisfying the first reference value.

The user may provide fingerprint data several times to the userauthentication apparatus 1 until the user authentication succeeds. Inaddition, the user may repeatedly attempt user authentication until theuser authentication succeeds. That is, some of the biometric dataobtained before the success biometric data may be estimated as biometricdata of the user. In addition, from among the biometric data obtained inthe process of using the user authentication apparatus 1, biometric datasimilar to the reference data may be estimated to be the biometric dataof the user. Therefore, by using the method shown in FIGS. 5 through 10,the controller 13 may add plural pieces of biometric data of the user tothe training data.

The previous biometric data and subsequent biometric data correspond tofailure biometric data. The controller 13 may secure reliable trainingdata by adding failure biometric data related to the success biometricdata to the training data, without adding all of the failure biometricdata to the training data.

By obtaining the training data according to the method with reference toFIGS. 5 through 10, the biometric data obtained in the userauthentication process of the user authentication apparatus 1 may beused as training data.

In the method of adding training data with reference to FIGS. 5 through10, fingerprint data is taken as an example for convenience ofexplanation, but other biometric data may be applied in a same manner.

Referring back to FIG. 4, in operation 405, the controller 13 may trainthe user authentication model by using the training data. Operation 405may include characteristics of operation 304 of FIG. 3.

In operation 406, the controller 13 may obtain new biometric data andperform user authentication based on the new biometric data by using thetrained user authentication model. In operation 406, the controller 13may perform user authentication by using the user authentication modelthat is trained or re-trained in operation 405.

As the user authentication model is trained on biometric data input inthe user authentication process, obstacles such as contamination of asensor and fingerprint changes may be reflected in the training.Accordingly, the user authentication apparatus 1 may perform userauthentication to be robust to the obstacles by using a userauthentication model.

FIG. 11 shows a user authentication method according to an embodiment.

Comparing the user authentication method of FIG. 11 to the userauthentication method of FIG. 4, operations 1101 through 1104 mayrespectively include characteristics of operations 401 through 404, andoperations 1106 through 1107 may respectively include characteristics ofoperations 405 through 406. To avoid repeated descriptions, onlyoperation 1105 will be described.

In operation 1105, the controller 13 may determine whether the userauthentication is to be trained.

For example, the controller 13 may determine whether training isrequired based on whether training data to train the user authenticationmodel is sufficiently obtained. If the number of pieces of training datais sufficient, or if the training data may be complimented by using dataaugmentation even though the number of pieces of training data isinsufficient, the controller 13 may determine that the userauthentication model needs to be trained.

For example, the controller 13 may determine whether training isrequired, based on a user recognition rate. When the number of failurebiometric data obtained immediately before obtaining the successbiometric data exceeds a predetermined number, the controller 13 maydetermine that the user authentication model needs to be trained. Whenthe number of pieces of failure biometric data obtained immediatelybefore obtaining the success biometric data is equal to or greater thanthe predetermined number, it may indicate that the user authenticationrate of the user authentication device 1 is low.

FIG. 12 is a block diagram illustrating hardware components of theaerosol generating device according to an embodiment.

Referring to FIG. 12, the aerosol generating device 10000 may include abattery 11000, a heater 12000, a sensor 13000, a user interface 14000, amemory 15000, and a controller 16000. However, the internal structure ofthe aerosol generating device 10000 is not limited to the structuresillustrated in FIG. 12. According to the design of the aerosolgenerating device 10000, it will be understood by one of ordinary skillin the art that some of the hardware components shown in FIG. 12 may beomitted or new components may be added.

In an embodiment, the aerosol generating device 10000 may be a devicefor generating aerosol by heating a cigarette. In another embodiment,the aerosol generating device 10000 may be a device for generatingaerosol by heating a liquid composition of a cartridge. In anotherembodiment, the aerosol generating device 10000 may be a device forgenerating aerosol by heating a cigarette and a liquid composition of acartridge.

In an embodiment, the aerosol generating device 10000 may consist ofonly a main body, in which case hardware components included in theaerosol generating device 10000 are located in the main body. In anotherembodiment, the aerosol generating device 10000 may consist of a mainbody and a cartridge, in which case hardware components included in theaerosol generating device 10000 are located separately in the main bodyand the cartridge. Alternatively, at least some of hardware componentsincluded in the aerosol generating device 10000 may be located in themain body and the cartridge, respectively.

Hereinafter, an operation of each of the components will be describedwithout being limited to location in a particular space in the aerosolgenerating device 10000 is located.

*104The battery 11000 supplies electric power to be used for the aerosolgenerating device 10000 to operate. In other words, the battery 11000may supply power such that the heater 12000 may be heated. In addition,the battery 11000 may supply power required for operation of otherhardware components included in the aerosol generating device 10000,that is, the sensor 13000, the user interface 14000, the memory 15000,and the controller 16000. The battery 11000 may be a rechargeablebattery or a disposable battery. For example, the battery 11000 may be alithium polymer (LiPoly) battery, but is not limited thereto.

The heater 12000 receives power from the battery 11000 under the controlof the controller 16000. The heater 12000 may receive power from thebattery 11000 and heat a cigarette inserted into the aerosol generatingdevice 10000, or heat the cartridge mounted on the aerosol generatingdevice 10000.

The heater 12000 may be located in the main body of the aerosolgenerating device 10000. Alternatively, when the aerosol generatingdevice 10000 consists of the main body and the cartridge, the heater12000 may be located in the cartridge. When the heater 12000 is locatedin the cartridge, the heater 12000 may receive power from the battery11000 located in at least one of the main body and the cartridge.

The heater 12000 may be formed of any suitable electrically resistivematerial. For example, the suitable electrically resistive material maybe a metal or a metal alloy including titanium, zirconium, tantalum,platinum, nickel, cobalt, chromium, hafnium, niobium, molybdenum,tungsten, tin, gallium, manganese, iron, copper, stainless steel, ornichrome, but is not limited thereto. In addition, the heater 12000 maybe implemented by a metal wire, a metal plate on which an electricallyconductive track is arranged, or a ceramic heating element, but is notlimited thereto.

In an embodiment, the heater 12000 may be a component included in thecartridge. The cartridge may include the heater 12000, the liquiddelivery element, and the liquid storage. The aerosol generatingmaterial accommodated in the liquid storage may be moved to the liquiddelivery element, and the heater 12000 may heat the aerosol generatingmaterial absorbed by the liquid delivery element, thereby generatingaerosol. For example, the heater 12000 may include a material such asnickel or chromium and may be wound around or arranged adjacent to theliquid delivery element.

In another embodiment, the heater 12000 may heat the cigarette insertedinto the accommodation space of the aerosol generating device 10000. Asthe cigarette is accommodated in the accommodation space of the aerosolgenerating device 10000, the heater 12000 may be located inside and/oroutside the cigarette. Accordingly, the heater 12000 may generateaerosol by heating the aerosol generating material in the cigarette.

Meanwhile, the heater 12000 may include an induction heater. The heater13000 may include an electrically conductive coil for heating acigarette or the cartridge in an induction heating method, and thecigarette or the cartridge may include a susceptor which may be heatedby the induction heater.

The aerosol generating device 10000 may include at least one sensor13000. A result sensed by the at least one sensor 13000 is transmittedto the controller 16000, and the controller 16000 may control theaerosol generating device 10000 to perform various functions such ascontrolling the operation of the heater, restricting smoking,determining whether a cigarette (or a cartridge) is inserted, anddisplaying a notification.

For example, the at least one sensor 13000 may include a puff detectingsensor. The puff detecting sensor may detect a user's puff based on anyone of a temperature change, a flow change, a voltage change, and apressure change.

In addition, the at least one sensor 13000 may include a temperaturesensor. The temperature sensor may detect a temperature at which theheater 12000 (or an aerosol generating material) is heated. The aerosolgenerating device 10000 may include a separate temperature sensor forsensing a temperature of the heater 12000, or the heater 12000 itselfmay serve as a temperature sensor instead of including a separatetemperature sensor. Alternatively, a separate temperature sensor may befurther included in the aerosol generating device 10000 while the heater12000 serves as a temperature sensor.

In addition, the at least one sensor 13000 may be used for obtainingbiometric data. The at least one sensor 13000 may be an image sensor, afingerprint sensor, an acoustic sensor, a temperature sensor, anelectro-optical sensor, a biometric sensor, an ultrasonic sensor, but isnot limited thereto.

The user interface 14000 may provide the user with information about thestate of the aerosol generating device 10000. The user interface 14000may include various interfacing devices, such as a display or a lightemitter for outputting visual information, a motor for outputting hapticinformation, a speaker for outputting sound information, input/output(I/O) interfacing devices (for example, a button or a touch screen) forreceiving information input from the user or outputting information tothe user, terminals for performing data communication or receivingcharging power, and communication interfacing modules for performingwireless communication (for example, Wi-Fi, Wi-Fi direct, Bluetooth,near-field communication (NFC), etc.) with external devices.

However, the aerosol generating device 10000 may be implemented byselecting only some of the above-described various interfacing devices.

The memory 15000 may be a hardware component configured to store variouspieces of data processed in the aerosol generating device 10000, and thememory 15000 may store data processed or to be processed by thecontroller 16000.

The memory 15000 may store an operation time of the aerosol generatingdevice 10000, the maximum number of puffs, the current number of puffs,at least one temperature profile, data on a user's smoking pattern, etc.

The controller 16000 is a hardware component configured to controlgeneral operations of the aerosol generating device 10000. Thecontroller 16000 may include at least one processor.

The controller 16000 analyzes a result of the sensing by at least onesensor 13000, and controls processes that are to be performedsubsequently.

The controller 16000 may control power supplied to the heater 12000 sothat the operation of the heater 12000 is started or terminated, basedon the result of the sensing by the at least one sensor 13000.

The controller 16000 may perform user authentication based on the userauthentication methods described with reference to FIGS. 2 through 11.The controller 16000 may perform user authentication based on biometricdata obtained through the at least one sensor 13000. When the userauthentication is successful, the controller 16000 may control powersupplied to the heater 12000 such that operations of the heater 12000are started. For example, when the user authentication is successful,the controller 16000 may control the power provided to the heater 12000such that the heater 12000 starts preheating.

In addition, based on the result of the sensing by the at least onesensor 13000, the controller 16000 may control the amount of powersupplied to the heater 12000 and the time at which the power issupplied, so that the heater 12000 is heated to a predeterminedtemperature or maintained at an appropriate temperature.

In an embodiment, the controller 16000 may set a mode of the heater12000 to a pre-heating mode to start the operation of the heater 12000after receiving a user input to the aerosol generating device 10000. Inaddition, the controller 16000 may switch the mode of the heater 12000from the pre-heating mode to an operation mode after detecting a user'spuff by using the puff detecting sensor. In addition, the controller16000 may stop supplying power to the heater 12000 when the number ofpuffs reaches a preset number after counting the number of puffs byusing the puff detecting sensor.

The controller 16000 may control the user interface 14000 based on theresult of the sensing by the at least one sensor 13000. For example,when the number of puffs reaches the preset number after counting thenumber of puffs by using the puff detecting sensor, the controller 16000may notify the user by using at least one of a light emitter, a motor ora speaker that the aerosol generating device 10000 will soon beterminated.

Although not illustrated in FIG. 12, an aerosol generating system may beconfigured by the aerosol generating device 10000 and a separate cradle.For example, the cradle may be used to charge the battery 11000 of theaerosol generating device 10000. For example, the aerosol generatingdevice 10000 may be supplied with power from a battery of the cradle tocharge the battery 11000 of the aerosol generating device 10000 whilebeing accommodated in an accommodation space of the cradle.

FIG. 13 shows an example in which a user uses an aerosol generatingdevice. FIG. 14 shows an example of a method, performed by an aerosolgenerating device, of authenticating a user.

Referring to FIGS. 13 and 14, an aerosol generating device 1300 may be adevice for generating aerosol by heating a cigarette and/or a liquidcomposition of a cartridge.

The aerosol generating device 1300 may include an input interfacingelement 1301 for obtaining a user input for controlling the aerosolgenerating device 1300. For example, the input interfacing element 1301may be a button, touch screen, or a touch pad. The user may controloperation of the aerosol-generating device 1300 by operating the inputinterfacing element 1301. For example, the user may control operationmodes of the aerosol generating device 1300 or may control a state ofthe aerosol generating device 1300 to be output via an outputinterfacing element, by adjusting the number and/or duration of touchingthe input interfacing element 1301.

The input interfacing element 1301 may include a fingerprint sensor.When a user brings a finger into contact with the input interfacingelement 1301, the user's fingerprint data may be obtained via thefingerprint sensor.

In operation 1401, a controller of the aerosol generating device 1300obtains fingerprint data. Operation 1401 may include characteristics ofoperation 401 shown in FIG. 4.

In operation 1402, the controller of the aerosol generating device 1300performs user authentication based on the obtained fingerprint data.Operation 1402 may include characteristics of operation 402 of FIG. 4.

In operation 1403, the controller of the aerosol generating device 1300determines whether the user authentication succeeds. The controllerrepeats operation 1401 when the user authentication fails, and performsoperation 1404 when the user authentication succeeds.

In operation 1404, the controller of the aerosol generating device 1300adds success fingerprint data to the training user, the successfingerprint data being fingerprint data that succeeded in userauthentication. Operation 1404 may include characteristics of operation404 of FIG. 4.

In operation 1405, the controller of the aerosol generating device 1300adds post fingerprint data to training data, the post fingerprint databeing fingerprint data obtained after the success fingerprint data.After the user authentication succeeds, the user may operate the inputinterfacing element 1301 for various reasons, for example, to controlthe aerosol generating device 1300. The user adds fingerprint dataobtained through the input interfacing element 1301 in the process ofusing the aerosol generating device 1300 to the training data, therebyadding a plurality of pieces of fingerprint data of the user to thetraining data.

For example, the controller may add the post fingerprint data having asimilarity equal to or greater than a predetermined value with thereference fingerprint data to the training data. For example, thecontroller may add a predetermined number of post fingerprint data tothe training data, the post fingerprint data being obtained after thesuccess fingerprint data. For example, the controller may add postfingerprint data obtained for a predetermined period after the successfingerprint data to the training data. For example, the controller mayadd post fingerprint data to the training data, the post fingerprintdata being obtained in a predetermined time interval after the successfingerprint data.

In operation 1406, the controller of the aerosol generating devicetrains the user authentication model by using the training data.Operation 1406 may include characteristics of operation 405 of FIG. 4.

Although the method of performing user authentication based on thefingerprint data is described in the embodiments with reference to FIGS.13 and 14, the method may be similarly applied to other biometric datathan the fingerprint data.

At least one of the components, elements, modules or units (collectively“components” in this paragraph) represented by a block in the drawings,such as the controller 13, the controller 16000, the sensor 13000 inFIGS. 1 and 12, may be embodied as various numbers of hardware, softwareand/or firmware structures that execute respective functions describedabove, according to an exemplary embodiment. For example, at least oneof these components may use a direct circuit structure, such as amemory, a processor, a logic circuit, a look-up table, etc. that mayexecute the respective functions through controls of one or moremicroprocessors or other control apparatuses. Also, at least one ofthese components may be specifically embodied by a module, a program, ora part of code, which contains one or more executable instructions forperforming specified logic functions, and executed by one or moremicroprocessors or other control apparatuses. Further, at least one ofthese components may include or may be implemented by a processor suchas a central processing unit (CPU) that performs the respectivefunctions, a microprocessor, or the like. Two or more of thesecomponents may be combined into one single component which performs alloperations or functions of the combined two or more components. Also, atleast part of functions of at least one of these components may beperformed by another of these components. Further, although a bus is notillustrated in the above block diagrams, communication between thecomponents may be performed through the bus. Functional aspects of theabove exemplary embodiments may be implemented in algorithms thatexecute on one or more processors. Furthermore, the componentsrepresented by a block or processing steps may employ any number ofrelated art techniques for electronics configuration, signal processingand/or control, data processing and the like.

The descriptions of the above-described embodiments are merely examples,and it will be understood by one of ordinary skill in the art thatvarious changes and equivalents thereof may be made. Therefore, thescope of the disclosure should be defined by the appended claims, andall differences within the scope equivalent to those described in theclaims will be construed as being included in the scope of protectiondefined by the claims.

1. A method of performing user authentication, the method comprising:obtaining biometric data; performing user authentication based on thebiometric data; adding the biometric data to training data after theperforming the user authentication; training, by using the trainingdata, a user authentication model that is a learning model configured toperform the user authentication; and performing the user authenticationbased on new biometric data by using the user authentication model. 2.The method of claim 1, wherein the adding comprises adding successbiometric data to the training data, the success biometric data beingthe biometric data that succeeded in the user authentication.
 3. Themethod of claim 2, wherein the adding comprises adding previousbiometric data to the training data, the previous biometric data beingbiometric data obtained before the success biometric data.
 4. The methodof claim 3, wherein the adding of the previous biometric data to thetraining data comprises adding a predetermined number of pieces of theprevious biometric data obtained immediately before the successbiometric data is obtained to the training data.
 5. The method of claim3, wherein the previous biometric data is biometric data obtained withina predetermined period before the success biometric data is obtained tothe training data.
 6. The method of claim 3, wherein the adding of theprevious biometric data to the training data comprises adding apredetermined number of pieces of the previous biometric data obtainedwithin a predetermined period before the success biometric data isobtained to the training data.
 7. The method of claim 3, wherein theadding of the previous biometric data to the training data comprisesadding a plurality of pieces of the previous biometric data which aresequentially obtained to the training data, and wherein each of a timeinterval between adding a piece of the previous biometric data to thetraining data and adding another piece of the previous biometric data tothe training data and a time interval between adding the successbiometric data to the training data and adding a piece of the previousbiometric data, obtained immediately before the success biometric data,to the training data is less than or equal to a predetermined timeinterval.
 8. The method of claim 1, wherein the adding comprises addingsimilar biometric data to the training data, the similar biometric databeing biometric data having a similarity equal to or greater than afirst reference value with reference data.
 9. The method of claim 8,wherein the performing of the user authentication comprises determiningthat the user authentication succeeded based on a similarity between thereference data and the obtained biometric data being equal to or greaterthan second reference value, wherein the second reference value isgreater than the first reference value.
 10. The method of claim 8,wherein the reference data is biometric data of a user obtained inadvance for the user authentication, and wherein the adding furthercomprises adding the reference data to the training data.
 11. The methodof claim 1, further comprising determining whether the userauthentication model needs to be trained, based on a user recognitionrate of the user authentication model or the number of the trainingdata.
 12. An apparatus for performing user authentication, the apparatuscomprising: a sensor configured to obtain biometric data; a memoryconfigured to store at least one program; and a controller configured toperform user authentication by executing the at least one program,wherein the at least one program comprises instructions to implementoperations of: performing the user authentication based on the obtainedbiometric data; adding the biometric data to training data afterperforming the user authentication; training, by using the trainingdata, a user authentication model that is a learning model configured toperform the user authentication; and performing the user authenticationbased on new biometric data by using the user authentication model. 13.The apparatus of claim 12, further comprising: a battery; and a heaterconfigured to receive power from the battery and heat an aerosolgenerating material, wherein the controller controls power supplied fromthe battery to the heater.
 14. The apparatus of claim 13, wherein thecontroller controls the power delivered to the heater, based on a resultof the user authentication.
 15. The apparatus of claim 13, furthercomprising an input interfacing element configured to obtain a userinput for controlling the apparatus, wherein the controller is configureto add biometric data, obtained by the input interfacing element aftersucceeding in the user authentication, to the training data.